Java Using Much More Memory Than Heap Size (Or Size Correctly Docker Memory Limit)

Java using much more memory than heap size (or size correctly Docker memory limit)

Virtual memory used by a Java process extends far beyond just Java Heap. You know, JVM includes many subsytems: Garbage Collector, Class Loading, JIT compilers etc., and all these subsystems require certain amount of RAM to function.

JVM is not the only consumer of RAM. Native libraries (including standard Java Class Library) may also allocate native memory. And this won't be even visible to Native Memory Tracking. Java application itself can also use off-heap memory by means of direct ByteBuffers.

So what takes memory in a Java process?

JVM parts (mostly shown by Native Memory Tracking)

1. Java Heap

The most obvious part. This is where Java objects live. Heap takes up to -Xmx amount of memory.

2. Garbage Collector

GC structures and algorithms require additional memory for heap management. These structures are Mark Bitmap, Mark Stack (for traversing object graph), Remembered Sets (for recording inter-region references) and others. Some of them are directly tunable, e.g. -XX:MarkStackSizeMax, others depend on heap layout, e.g. the larger are G1 regions (-XX:G1HeapRegionSize), the smaller are remembered sets.

GC memory overhead varies between GC algorithms. -XX:+UseSerialGC and -XX:+UseShenandoahGC have the smallest overhead. G1 or CMS may easily use around 10% of total heap size.

3. Code Cache

Contains dynamically generated code: JIT-compiled methods, interpreter and run-time stubs. Its size is limited by -XX:ReservedCodeCacheSize (240M by default). Turn off -XX:-TieredCompilation to reduce the amount of compiled code and thus the Code Cache usage.

4. Compiler

JIT compiler itself also requires memory to do its job. This can be reduced again by switching off Tiered Compilation or by reducing the number of compiler threads: -XX:CICompilerCount.

5. Class loading

Class metadata (method bytecodes, symbols, constant pools, annotations etc.) is stored in off-heap area called Metaspace. The more classes are loaded - the more metaspace is used. Total usage can be limited by -XX:MaxMetaspaceSize (unlimited by default) and -XX:CompressedClassSpaceSize (1G by default).

6. Symbol tables

Two main hashtables of the JVM: the Symbol table contains names, signatures, identifiers etc. and the String table contains references to interned strings. If Native Memory Tracking indicates significant memory usage by a String table, it probably means the application excessively calls String.intern.

7. Threads

Thread stacks are also responsible for taking RAM. The stack size is controlled by -Xss. The default is 1M per thread, but fortunately the things are not so bad. OS allocates memory pages lazily, i.e. on the first use, so the actual memory usage will be much lower (typically 80-200 KB per thread stack). I wrote a script to estimate how much of RSS belongs to Java thread stacks.

There are other JVM parts that allocate native memory, but they do not usually play a big role in total memory consumption.

Direct buffers

An application may explicitly request off-heap memory by calling ByteBuffer.allocateDirect. The default off-heap limit is equal to -Xmx, but it can be overridden with -XX:MaxDirectMemorySize. Direct ByteBuffers are included in Other section of NMT output (or Internal before JDK 11).

The amount of used direct memory is visible through JMX, e.g. in JConsole or Java Mission Control:

Besides direct ByteBuffers there can be MappedByteBuffers - the files mapped to virtual memory of a process. NMT does not track them, however, MappedByteBuffers can also take physical memory. And there is no a simple way to limit how much they can take. You can just see the actual usage by looking at process memory map: pmap -x <pid>

Address           Kbytes    RSS    Dirty Mode  Mapping
...
00007f2b3e557000   39592   32956       0 r--s- some-file-17405-Index.db
00007f2b40c01000   39600   33092       0 r--s- some-file-17404-Index.db
                           ^^^^^               ^^^^^^^^^^^^^^^^^^^^^^^^

Native libraries

JNI code loaded by System.loadLibrary can allocate as much off-heap memory as it wants with no control from JVM side. This also concerns standard Java Class Library. In particular, unclosed Java resources may become a source of native memory leak. Typical examples are ZipInputStream or DirectoryStream.

JVMTI agents, in particular, jdwp debugging agent - can also cause excessive memory consumption.

This answer describes how to profile native memory allocations with async-profiler.

Allocator issues

A process typically requests native memory either directly from OS (by mmap system call) or by using malloc - standard libc allocator. In turn, malloc requests big chunks of memory from OS using mmap, and then manages these chunks according to its own allocation algorithm. The problem is - this algorithm can lead to fragmentation and excessive virtual memory usage.

jemalloc, an alternative allocator, often appears smarter than regular libc malloc, so switching to jemalloc may result in a smaller footprint for free.

Conclusion

There is no guaranteed way to estimate full memory usage of a Java process, because there are too many factors to consider.

Total memory = Heap + Code Cache + Metaspace + Symbol tables +
               Other JVM structures + Thread stacks +
               Direct buffers + Mapped files +
               Native Libraries + Malloc overhead + ...

It is possible to shrink or limit certain memory areas (like Code Cache) by JVM flags, but many others are out of JVM control at all.

One possible approach to setting Docker limits would be to watch the actual memory usage in a "normal" state of the process. There are tools and techniques for investigating issues with Java memory consumption: Native Memory Tracking, pmap, jemalloc, async-profiler.

Update

Here is a recording of my presentation Memory Footprint of a Java Process.

In this video, I discuss what may consume memory in a Java process, how to monitor and restrain the size of certain memory areas, and how to profile native memory leaks in a Java application.

Java memory settings in a docker container

whether, in general terms, setting the -Xmx setting is too high for a container whose memory limit is 20GB

It depends. An application can use less RAM than the specified -Xmx, as well as 2x or 3x more RAM than the specified -Xmx. I've seen many applications of both kinds.

See what takes memory in a Java process.

Instead of trying to guess an appropriate heap size basing on the given container limit (those can be completely unrelated), why don't you set -Xmx to the value, which is comfortable enough for your particular application? I mean, if your application works fine with just 8 GB heap, there is no need to give it more, even if the container permits.

Is it generally the case that you use either MaxRAM or -Xmx, or is there any benefit to setting both?

Setting both is meaningless, as Xmx overrides MaxRAM.

I were to use MaxRAM instead of -Xmx, how would java allocate memory to the heap? Is there a simple algorithm for this, for example, 50% of the MaxRAM setting?

See What is the difference between xmx and MaxRAM JVM parameters?

Will java manage memory any more efficiently doing it that way?

No. MaxRAM only affects calculation of the heap size and the default garbage collector (when not explicitly specified).

How to determine which memory to use for a certain service heap memory?

The exact amount of memory needed for the heap is very specific to the application - you are better of trying multiple configurations and see yourself.

However, needing 4 GB for something that consumes about 600 MB is quite unusual. What are the other things that consume the host memory?

Note that JVM uses much more than just heap memory and this again can vary a lot from application to application.
For an overview of various types of memory used by JVM I recommend this excellent answer: Java using much more memory than heap size (or size correctly Docker memory limit)

Finally, you can adjust the default allocation strategy (25% of available RAM) via -XX:MaxRAMPercentage flag - I typically set this to 60%, but for sure measure first!

Docker - Java container doesn't respect memory limits

To restrict memory for docker containers, you need to add following in your docker-compose.yml file

environment:
  - <name>=<value>
deploy:
  resources:
    memory: 256M

Once you add the above code, then containers would be restricted to given memory limit and you can see the result in docker stats output. For more details about the resource restriction refer this docker documentation.

Note: If the container crosses the given memory limit, the kernel will kill the container.

G1 GC allocated memory is more than heap size

This is your JVM parameters ,the number is byte. 23923261440(byte) = 22815(Mb) = 22.28(Gb)

-XX:InitialHeapSize=23923261440
-XX:MaxHeapSize=23923261440

By default, the space of G1's Young Gen and Old Gen is not fixed.From the Interactive Graphs column of the GCEasy page you shared,
I have organized the following information in a timeline.

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